diff --git a/src/gfn/__init__.py b/src/gfn/__init__.py
index a521e9f6..1010066c 100644
--- a/src/gfn/__init__.py
+++ b/src/gfn/__init__.py
@@ -1,3 +1,6 @@
 import importlib.metadata as met
+import logging
 
 __version__ = met.version("torchgfn")
+
+logging.getLogger(__name__).addHandler(logging.NullHandler())
diff --git a/src/gfn/gym/diffusion_sampling.py b/src/gfn/gym/diffusion_sampling.py
index 68fc5385..53c117dd 100644
--- a/src/gfn/gym/diffusion_sampling.py
+++ b/src/gfn/gym/diffusion_sampling.py
@@ -1,3 +1,4 @@
+import logging
 import math
 import os
 from abc import ABC, abstractmethod
@@ -16,6 +17,8 @@
 from gfn.states import States
 from gfn.utils.common import filter_kwargs_for_callable, temporarily_set_seed
 
+logger = logging.getLogger(__name__)
+
 # Lightweight typing alias for the target registry entries.
 TargetEntry = tuple[type["BaseTarget"], dict[str, Any]]
 
@@ -215,9 +218,9 @@ def __init__(
         )
         mixture_weights = mixture_weights / mixture_weights.sum()
 
-        print("+ Gaussian Mixture Target initialization:")
-        print("+ num_components: ", num_components)
-        print("+ mixture_weights: ", mixture_weights)
+        logger.info("+ Gaussian Mixture Target initialization:")
+        logger.info(f"+ num_components: {num_components}")
+        logger.info(f"+ mixture_weights: {mixture_weights}")
         for i, (loc, cov) in enumerate(zip(locs, covariances)):
             loc_str = np.array2string(loc, precision=2, separator=", ").replace(
                 "\n", " "
@@ -225,7 +228,7 @@ def __init__(
             cov_str = np.array2string(cov, precision=2, separator=", ").replace(
                 "\n", " "
             )
-            print(f"\tComponent {i+1}: loc={loc_str}, cov={cov_str}")
+            logger.info(f"\tComponent {i+1}: loc={loc_str}, cov={cov_str}")
 
         # Convert to torch tensors
         dtype = torch.get_default_dtype()
@@ -719,8 +722,10 @@ def __init__(
             target_cls.__init__,
             {**default_kwargs, **(target_kwargs or {})},
         )
-        print("DiffusionSampling:")
-        print(f"+ Initalizing target {target_cls.__name__} with kwargs: {merged_kwargs}")
+        logger.info("DiffusionSampling:")
+        logger.info(
+            f"+ Initalizing target {target_cls.__name__} with kwargs: {merged_kwargs}"
+        )
         self.target = target_cls(device=device, **merged_kwargs)
 
         self.dim = self.target.dim
@@ -779,9 +784,9 @@ def list_available_targets(cls) -> dict[str, dict[str, Any]]:
         target class's constructor signature.
         """
         out = {}
-        print("Available DiffusionSampling targets:")
+        logger.info("Available DiffusionSampling targets:")
         for alias, (cls, defaults) in cls.DIFFUSION_TARGETS.items():
-            print(f"+ {alias}: {cls.__name__} with kwargs: {defaults}")
+            logger.info(f"+ {alias}: {cls.__name__} with kwargs: {defaults}")
             out[alias] = {"class": cls.__name__, "defaults": dict(defaults)}
 
         return out
diff --git a/src/gfn/gym/hypergrid.py b/src/gfn/gym/hypergrid.py
index 9196aa11..f47d24dd 100644
--- a/src/gfn/gym/hypergrid.py
+++ b/src/gfn/gym/hypergrid.py
@@ -1,9 +1,9 @@
 """Adapted from https://github.com/Tikquuss/GflowNets_Tutorial"""
 
 import itertools
+import logging
 import multiprocessing
 import platform
-import warnings
 from abc import ABC, abstractmethod
 from decimal import Decimal
 from functools import reduce
@@ -17,6 +17,8 @@
 from gfn.env import DiscreteEnv
 from gfn.states import DiscreteStates
 
+logger = logging.getLogger(__name__)
+
 if platform.system() == "Windows":
     multiprocessing.set_start_method("spawn", force=True)
 else:
@@ -86,7 +88,7 @@ def __init__(
             debug: If True, emit States with debug guards (not compile-friendly).
         """
         if height <= 4:
-            warnings.warn("+ Warning: height <= 4 can lead to unsolvable environments.")
+            logger.warning("+ Warning: height <= 4 can lead to unsolvable environments.")
 
         reward_functions = {
             "original": OriginalReward,
@@ -123,10 +125,10 @@ def __init__(
 
         if self.store_all_states:
             assert self._all_states_tensor is not None
-            print(f"+ Environment has {len(self._all_states_tensor)} states")
+            logger.info(f"+ Environment has {len(self._all_states_tensor)} states")
         if self.calculate_partition:
             assert self._log_partition is not None
-            print(f"+ Environment log partition is {self._log_partition}")
+            logger.info(f"+ Environment log partition is {self._log_partition}")
 
         if isinstance(device, str):
             device = torch.device(device)
@@ -414,7 +416,7 @@ def _enumerate_all_states_tensor(self, batch_size: int = 20_000):
                     total_rewards += self.reward_fn(batch_tensor).sum().item()
             end_time = time()
 
-            print(
+            logger.info(
                 "Enumerated all states in {} minutes".format(
                     (end_time - start_time) / 60.0,
                 )
diff --git a/src/gfn/modules.py b/src/gfn/modules.py
index fe847cf7..c8e4f797 100644
--- a/src/gfn/modules.py
+++ b/src/gfn/modules.py
@@ -1,10 +1,10 @@
-import warnings
+import logging
 
-warnings.warn(
+logger = logging.getLogger(__name__)
+
+logger.warning(
     "'modules.py' is deprecated and will be removed in a future release. Please import "
-    "from 'estimators.py' instead.",
-    DeprecationWarning,
-    stacklevel=2,
+    "from 'estimators.py' instead."
 )
 
 from gfn.estimators import (  # noqa: F401, E402
diff --git a/src/gfn/states.py b/src/gfn/states.py
index ce881a93..f679d34c 100644
--- a/src/gfn/states.py
+++ b/src/gfn/states.py
@@ -1,7 +1,7 @@
 from __future__ import annotations  # This allows to use the class name in type hints
 
 import inspect
-import warnings
+import logging
 from abc import ABC
 from math import prod
 from typing import (
@@ -25,9 +25,7 @@
 from gfn.utils.common import ensure_same_device
 from gfn.utils.graphs import GeometricBatch, get_edge_indices
 
-warnings.filterwarnings(
-    "once", message="Inconsistent conditions when extending states. Setting to None."
-)
+logger = logging.getLogger(__name__)
 
 
 def _assert_factory_accepts_debug(factory: Callable, factory_name: str) -> None:
@@ -373,7 +371,7 @@ def __setitem__(
             self.conditions[index] = states.conditions
         else:
             if self.conditions is not None or states.conditions is not None:
-                warnings.warn(
+                logger.warning(
                     "Inconsistent conditions when setting states. Setting to None."
                 )
             self.conditions = None
@@ -439,7 +437,7 @@ def extend(self, other: States) -> None:
             )
         else:
             if self.conditions is not None or other.conditions is not None:
-                warnings.warn(
+                logger.warning(
                     "Inconsistent conditions when extending states. Setting to None."
                 )
             self.conditions = None
@@ -832,7 +830,7 @@ def extend(self, other: DiscreteStates) -> None:
         else:
             # Inconsistent, raise a warning and set to None
             if self.conditions is not None or other.conditions is not None:
-                warnings.warn(
+                logger.warning(
                     "Inconsistent conditions when extending states. Setting to None."
                 )
             self.conditions = None
@@ -1495,7 +1493,7 @@ def __setitem__(
             self.conditions[index] = graph.conditions
         else:
             if self.conditions is not None or graph.conditions is not None:
-                warnings.warn(
+                logger.warning(
                     "Inconsistent conditions when setting states. Setting to None."
                 )
             self.conditions = None
@@ -1600,7 +1598,7 @@ def extend(self, other: GraphStates):
             )
         else:
             if self.conditions is not None or other.conditions is not None:
-                warnings.warn(
+                logger.warning(
                     "Inconsistent conditions when extending states. Setting to None."
                 )
             self.conditions = None
diff --git a/src/gfn/utils/common.py b/src/gfn/utils/common.py
index 5c7fd44d..dc4ec157 100644
--- a/src/gfn/utils/common.py
+++ b/src/gfn/utils/common.py
@@ -1,9 +1,9 @@
 import inspect
+import logging
 import os
 import random
 import threading
 import time
-import warnings
 from contextlib import contextmanager
 from typing import Any, Callable, Tuple
 
@@ -11,6 +11,8 @@
 import torch
 import torch.distributed as dist
 
+logger = logging.getLogger(__name__)
+
 # -----------------------------------------------------------------------------
 # Utility helpers
 # -----------------------------------------------------------------------------
@@ -249,9 +251,8 @@ def set_seed(seed: int, deterministic_mode: bool = False) -> None:
             torch.use_deterministic_algorithms(True)
         except AttributeError:
             # Older PyTorch (<1.8) fallback: do nothing.
-            warnings.warn(
-                "PyTorch is older than 1.8, deterministic algorithms are not supported.",
-                UserWarning,
+            logger.warning(
+                "PyTorch is older than 1.8, deterministic algorithms are not supported."
             )
 
         # CPU-specific settings for non-distributed case
diff --git a/src/gfn/utils/compile.py b/src/gfn/utils/compile.py
index d772a503..b5263152 100644
--- a/src/gfn/utils/compile.py
+++ b/src/gfn/utils/compile.py
@@ -1,9 +1,12 @@
 from __future__ import annotations
 
+import logging
 from typing import Iterable
 
 import torch
 
+logger = logging.getLogger(__name__)
+
 
 def try_compile_gflownet(
     gfn,
@@ -52,4 +55,4 @@ def try_compile_gflownet(
     formatted = ", ".join(
         f"{name}:{'✓' if success else 'x'}" for name, success in results.items()
     )
-    print(f"[compile] {formatted}")
+    logger.info(f"[compile] {formatted}")
diff --git a/src/gfn/utils/distributed.py b/src/gfn/utils/distributed.py
index 08bbf9b2..7be84a52 100644
--- a/src/gfn/utils/distributed.py
+++ b/src/gfn/utils/distributed.py
@@ -255,10 +255,13 @@ def initialize_distributed_compute(
     training_ranks = [
         r for r in range(num_training_ranks)
     ]  # e.g., 0..num_training_ranks-1
-    train_global_group = dist.new_group(
-        ranks=training_ranks,
-        backend=dist_backend,
-        timeout=datetime.timedelta(minutes=5),
+    train_global_group = cast(
+        Optional[dist.ProcessGroup],
+        dist.new_group(
+            ranks=training_ranks,
+            backend=dist_backend,
+            timeout=datetime.timedelta(minutes=5),
+        ),
     )
 
     buffer_group = None
@@ -268,10 +271,13 @@ def initialize_distributed_compute(
         buffer_ranks = list(
             range(num_training_ranks, num_training_ranks + num_remote_buffers)
         )
-        buffer_group = dist.new_group(
-            buffer_ranks,
-            backend=dist_backend,
-            timeout=datetime.timedelta(minutes=5),
+        buffer_group = cast(
+            Optional[dist.ProcessGroup],
+            dist.new_group(
+                buffer_ranks,
+                backend=dist_backend,
+                timeout=datetime.timedelta(minutes=5),
+            ),
         )
         logger.info("Buffer group ranks: %s", buffer_ranks)
 
diff --git a/src/gfn/utils/handlers.py b/src/gfn/utils/handlers.py
index 74e3905e..fd5aaecc 100644
--- a/src/gfn/utils/handlers.py
+++ b/src/gfn/utils/handlers.py
@@ -1,9 +1,11 @@
-import warnings
+import logging
 from contextlib import contextmanager
 from typing import Any
 
 from gfn.containers import Container
 
+logger = logging.getLogger(__name__)
+
 
 @contextmanager
 def has_conditions_exception_handler(
@@ -19,8 +21,8 @@ def has_conditions_exception_handler(
     try:
         yield
     except TypeError as e:
-        print(f"conditions was passed but {target_name} is {type(target)}")
-        print(f"error: {str(e)}")
+        logger.error(f"conditions was passed but {target_name} is {type(target)}")
+        logger.error(f"error: {str(e)}")
         raise
 
 
@@ -38,8 +40,8 @@ def no_conditions_exception_handler(
     try:
         yield
     except TypeError as e:
-        print(f"conditions was not passed but {target_name} is {type(target)}")
-        print(f"error: {str(e)}")
+        logger.error(f"conditions was not passed but {target_name} is {type(target)}")
+        logger.error(f"error: {str(e)}")
         raise
 
 
@@ -57,7 +59,9 @@ def is_callable_exception_handler(
     try:
         yield
     except:  # noqa
-        print(f"conditions was passed but {target_name} is not callable: {type(target)}")
+        logger.error(
+            f"conditions was passed but {target_name} is not callable: {type(target)}"
+        )
         raise
 
 
@@ -72,7 +76,7 @@ def warn_about_recalculating_logprobs(
         recalculate_all_logprobs: Whether to recalculate all logprobs.
     """
     if recalculate_all_logprobs and obj.has_log_probs:
-        warnings.warn(
+        logger.warning(
             "Recalculating logprobs for a container that already has them. "
             "This might be intended, if the log_probs were calculated off-policy. "
             "However, this is inefficient when training on-policy. In this case, "
diff --git a/src/gfn/utils/training.py b/src/gfn/utils/training.py
index b617a93b..5679cbe1 100644
--- a/src/gfn/utils/training.py
+++ b/src/gfn/utils/training.py
@@ -1,4 +1,4 @@
-import warnings
+import logging
 from typing import Dict, Iterable, Optional, Tuple
 
 import torch
@@ -11,17 +11,17 @@
 from gfn.samplers import Trajectories
 from gfn.states import DiscreteStates
 
+logger = logging.getLogger(__name__)
+
 
 def get_terminating_state_dist(
     env: DiscreteEnv,
     states: DiscreteStates,
 ) -> torch.Tensor:
     """[DEPRECATED] Use `env.get_terminating_state_dist(states)` instead."""
-    warnings.warn(
+    logger.warning(
         "gfn.utils.training.get_terminating_state_dist is deprecated; "
-        "use DiscreteEnv.get_terminating_state_dist(states) instead.",
-        DeprecationWarning,
-        stacklevel=2,
+        "use DiscreteEnv.get_terminating_state_dist(states) instead."
     )
     return env.get_terminating_state_dist(states)
 
@@ -33,10 +33,8 @@ def validate(
     visited_terminating_states: Optional[DiscreteStates] = None,
 ) -> Tuple[Dict[str, float], DiscreteStates | None]:
     """[DEPRECATED] Use `env.validate(gflownet, ...)` instead."""
-    warnings.warn(
-        "gfn.utils.training.validate is deprecated; use DiscreteEnv.validate(...) instead.",
-        DeprecationWarning,
-        stacklevel=2,
+    logger.warning(
+        "gfn.utils.training.validate is deprecated; use DiscreteEnv.validate(...) instead."
     )
     return env.validate(
         gflownet=gflownet,